Facial recognition: Will a future criminal be wearing your face?

Chris Middleton asks whether technologies such as Face++ point towards a future of ultimate security and conformity, or entirely new types of crime.

The near future will see humans engaged in a high-stakes face-off against AI. Here’s why.

DNA and fingerprints aside, the human face is regarded as the ultimate piece of Personally Identifiable Data (PID). It’s certainly the easiest for us to use: we’re all hardwired to recognise faces, both in the real world and in 2D recordings of them, which is why a technology that’s nearly two centuries old, photography, still grants us access to offices, international travel, and more, via our passports, driving licences, and ID cards.

But the new industrial age of robotics, AI, and big data isn’t interested in 2D anymore; it wants to delve deeper into our appearance, via technologies that are similar to those used in movies to motion-capture actors’ performances.

As AI, big data, and the Internet of Things rise, 3D facial recognition technologies are the new hotspot: computers and robots are being trained to recognise people from every angle, and authentication is the key application. Soon – as in the 2002 film Minority Report – personalised services and adverts may be triggered by scans of our faces in shops and public spaces, allowing us to access transport networks, visitor attractions, and more.

In such a future, some people may choose to hide their faces or block their cameras to shut out the advertising noise, while others may happily pose for the camera to join in-store loyalty programmes and gain access to free wifi, special offers, and more. Omni-channel services will increasingly rely on being able to recognise us via the cameras on our phones, while brands may use customers’ faces to advertise products: it will be up to users to read the Ts and Cs.

Chinese whispers

Apple and Vivo are among the companies already using facial recognition as security/login systems on mobiles, but one company has gone much further and sees the human face as the ultimate focal point for AI-enabled personalised services.

Face++ describes itself as a cognitive services provider. The billion-dollar startup and platform is owned by Chinese AI giant Megvii, whose deep-learning technologies allow Face++ to focus in on the minute details, movements, and nuances of a face that make personal identification more reliable and secure.

The breadth of these applications reveals just how prevalent facial recognition technologies will become over the next ten years, using deep scans of faces to unlock banking, shopping, dating, travel, and other applications, replacing credit/debit cards as a secure transaction platform. Other companies are rushing to catch up, such as China’s most popular search engine, Baidu.

Service with a smile

Several retailers in China are already moving towards ‘payment with a smile’: a customer stands in front of an in-store camera, smiles, and money is deducted from their account. It’s the smile that’s the clincher in ID terms, with the subtle movements of facial muscles providing an extra layer of security and accuracy.

How this might work with angry customers is a moot point, while doppelgangers, identical twins, botox, and plastic surgery may pose further problems to the system, but deep scans are designed to uncover subtleties that aren’t obvious to the naked eye. Even so, not everyone is comfortable in front of the camera – sometimes for mental health reasons – and so any forced application of the technology may push some customers away.

In vast, populous societies such as China, where ID is critical, the internet is regulated, and citizen behaviour is more tightly controlled than in the West, technologies like Face++ are able to catch on more quickly, and people’s preferences may be logged en masse over time. Soon, Chinese consumers may be what they eat, use, and buy in the eyes of technology platforms that are fed with citizen data, linked to their physical appearance.

And it stands to reason that, in any such society, some services or products could be denied to them, too, based on their personal profiles – and, potentially, a scan of their face and body. Citizen behaviour controlled at the checkout: who would bet against it?

Some Face++ applications have obvious social or healthcare benefits. For example, ‘skin status evaluation’ is at the beta stage, says the company. It uses deep learning to detect skin problems, such as acne or early-stage cancers, and can be linked to personalised recommendations and treatments.

Body detection, body outlining, and gesture recognition are also at an advanced stage, says Face++, enabling developers to detect body shapes and behaviours from a mass of raw camera data, while ‘gaze estimation’ tracks how the human eye moves around a screen. Inevitably, this will be used to push advertising at consumers, based on how they’re using apps or online services.

Coupled with emotion recognition, this technology could be disruptive in countless ways, or simply intrusive. A number of companies in the West are developing similar gaze/emotion tracking systems, such as Affectiva, nViso, and Emteq.

The beauty challenge

Others applications are perhaps more troubling.

‘Beauty Score’ is another Face++ technology that’s at the beta stage. It applies machine learning to evaluate a person’s attractiveness, says the company, and can recommend makeup to ‘improve’ their appearance, and link individuals to their ideal matches online – statements that suggest the technology will be used to objectify women, or push them towards conforming to social norms or to standards set by the fashion and beauty industry. In the post-Weinstein age, such AI-enabled behaviours would not go unchallenged in the West.

The underlying problem with Face++’s Beauty Score application is that it makes implicit assumptions about what beauty is (and isn’t), and what attributes people are attracted to. This ignores the fact that the concept of beauty is subjective, mutable, local, culturally diverse, and changes constantly over time.

Will the technology reflect that diversity, or simply reflect the preferences of its designers? This is a more important question than many people realise, because it has already been demonstrated that AI tends to reflect its designers’ choice of training data when it comes to assessing human ideals, such as beauty, as this report explains.

One long-term effect of the application may be that people may begin to conform to machine-generated concepts of beauty, while vulnerable people may believe that they aren’t attractive enough because a machine has told them so. Eating disorders, anxiety, depression, and cyber-bullying are already endemic among young people; a ‘beauty score’ seems likely to deepen these problems.

Abuses of the system

Throw more AI and predictive analytics into the mix, and it’s clear that any such system could also be open to abuse. Facial recognition and AI systems have already been used experimentally to predict if people have particular illnesses, and even to determine their sexual orientation from a photograph.

While discrimination against most minority groups is illegal in many countries, algorithm-based discrimination would be much harder to detect, and could open the floodgates to invisibly automated bias within certain industries, such as life insurance.

Sadly, fears about bias, discrimination, and lack of diversity are far from scaremongering when it comes to AI. For example, the Face++ system itself can be used to ‘beautify’ video footage, says the company, and one of its key algorithms is ‘skin whitening’. The implications of that capability alone are alarming.

The Face/off scenario

So do technologies such as Face++ point towards a future of ultimate security and personalisation? Or to a society of automated bias, conformity, and control at the checkout – a monoculture based on superficial appearances? (“I’m sorry, sir, our body scan indicates your BMI is poor, and our facial scan suggests you may have diabetes: we cannot sell you that product. Alternatively, click to accept this higher life insurance premium.”)

And there’s another question: is the system foolproof? Bizarre and unlikely though it may seem, another technology may be poised to throw a spanner in the works: 3D printing.

Real-F and Thatsmyface.com are among the companies that are enabling customers to have their own – or other people’s – faces 3D printed onto a variety of items. These include realistic, wearable masks of the kind that recall another movie, Mission Impossible. (A third Hollywood blockbuster, Face/off, featured two characters wearing each other’s faces.)

The underlying technology is exactly the same as facial recognition: a deep 3D scan of a person’s face, down to the microscopic details that add realism, but realistic masks can also be generated from multiple high-res photographs, say the companies.

Real-F, in particular, is focusing on absolute realism. The English-language version of the website says (in poor English): “The REALFACE looks exactly like the original face based on [a] technique called 3DPF (Three-Dimensional Photo Form).

“Our original 3PDF technique […] makes it possible to duplicate skin texture, the eye blood vessels and iris, and even your eye appeal exactly the same as the originals which an ordinal [sic] portrait can’t do. If you are thinking to leave a memory of yourself or your loved one, the REALFACE is the best fit.”

The company says it is developing realistic soft skin for its masks, too, and – from the examples on the website, at least – the results seem extraordinarily realistic (see picture).

As with Face++, some applications of 3D printing faces and other body parts could be transformative, in every sense, such as the ability to create a replacement face for someone who has been disfigured by illness or accident. Primitive versions of the technology have already been used in a handful of cases to do just that.

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But how long will it be before someone uses the same technology to fool facial recognition systems by using a realistic mask of someone else’s face? And how long before someone commits a crime using a stranger’s face – perhaps yours? The idea isn’t as far-fetched as it sounds.

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But how long will it be before someone uses the same technology to fool facial recognition systems by using a realistic mask of someone else’s face? And how long before someone commits a crime using a stranger’s face – perhaps yours? The idea isn’t as far-fetched as it sounds.

It was Isaac Newton who observed that every action carries an equal and opposite reaction. He was describing classical mechanics, but the principle applies in the virtual world too, as every internet security company that is engaged in an arms race with hackers knows: threats evolve as security evolves.

On the face of it, the relentless march of technology might appear to be making it harder for people to fool the system, but as this fake video of President Obama giving a speech proves, the same technologies can also be used to fool the public. The footage is faked using AI and CGI, and yet is extremely convincing.

So, welcome to the future. Should we look into the lens and face it with a smile? Or frown, pull up our coat collars, and walk the other way? One thing is clear: it’s time to decide.

About the author

Chris Middleton

Chris Middleton is one of the UK’s leading business & IT journalists and magazine editors. He is founder of Strategist magazine, consulting editor and former editor of Computing. He is also the former editor of: Computer Business Review (CBR). He is the author of several books on the creative use of digital media, and has commissioned, edited, and/or contributed to at least 50 more.
Unusually, Chris is one of the few private individuals in the UK to own a real humanoid robot, which he hires out to schools, colleges, and corporate clients. Robotics and AI are now core areas of Chris’ journalism.

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Outro

Science and technology are the principal drivers of human progress. The creation of technology is hindered by many problems including cost, access to expertise, counter productive attitudes to risk, and lack of iterative multi-disciplinary collaboration. We believe that the failure of technology to properly empower organisations is due to a misunderstanding of the nature of the software creation process, and a mismatch between that process and the organisational structures that often surround it.